Colloquium IS (September 7, 2018) – Factors that complicate selecting software requirements

Dear all,

We are pleased to invite you to our next Colloquium IS that will take place on Friday,

September 7, 2018, 16:00 – 17:00 (Paviljoen K.16).

Speaker: Hans Schoenmakers

Title: Factors that complicate selecting software requirements

Subtitle: Validating Factors from Literature in an Empirical Study

Abstract:

In market-driven software product development, new features may be added to the software, based on a collection of candidate requirements. Selecting requirements  however is difficult. Despite all work done on this problem, known as the next release problem, what is missing, is a comprehensive overview of the factors that complicate selecting software requirements. The research consists of a systematic literature review, searching for occurrences in the literature where a causal relation was suggested between certain conditions and the difficulty of selecting software requirements. Clustering the 156 findings, found by analyzing 544 papers, led to 33 complicating factors that were classified in eight groups. The complicating factors were validated in semi-structured interviews with twelve experts from three different industrial organizations. In these interviews both questions on experiences with the complicating factors and on why they were complicating were asked. The results aid in getting a better understanding of the complexity of selecting requirements.

 

 

Colloquium IS (July 6, 2018) – Discovering Anomalous Frequent Patterns from Event Logs

Dear all,

We are pleased to invite you to our next Colloquium IS that will take place on Friday,

July 6, 2018, 16:00 – 17:00 (Paviljoen K.16).

Speaker: dr. Laura Genga

Title: Discovering Anomalous Frequent Patterns from Event Logs

Abstract:

Conformance checking allows organizations to compare process executions recorded by the IT system against a process model representing the normative behavior. Most of the existing techniques, however, are only able to pinpoint where individual process executions deviate from the normative behavior, without considering neither possible correlations among occurred deviations nor their frequency. Moreover, possible parallelisms among process activities are usually neglected,

which can lead to inaccurate diagnostics. In this talk, I will introduce an approach to extract anomalous frequent patterns from historical logging data. The extracted patterns can exhibit parallel behaviors and correlate recurrent deviations that have occurred in possibly different portions of the process, thus providing the analysts with a valuable aid in investigating nonconforming behaviors. The approach has been evaluated using both synthetic and real-life logs.